Melanogenesis in visceral tissues of <i>Salmo salar</i>. A link between immunity and pigment production?
Bibliographic record
Abstract
Melanogenesis is mostly studied in melanocytes and melanoma cells, but much less is known about other pigment cell systems. Liver, spleen, kidney, and other organs of lower vertebrates harbour a visceral pigment cell system with an embryonic origin that differs from that of melanocytes. In teleosts, melanin-containing cells occur in the reticulo-endothelial system and are mainly in the kidney and spleen. The Atlantic salmon (Salmo salar L.) is an ichthyic breeding species of considerable economic importance. The accumulation of pigments in salmon visceral organs and musculature adversely affects the quality of fish products and is a problem for the aquaculture industry. With the aim to reveal novel functions and behaviour of the salmonid extracutaneous pigment system, we investigated aspects of the melanogenic systems in the tissues of Atlantic salmon, as well as in SHK-1 cells, which is a long-term cell line derived from macrophages of the Atlantic salmon head-kidney. We demonstrate that a melanogenic system is present in SHK-1 cells, head-kidney, and spleen tissues. As teleosts lack lymph nodes and Peyer's patches, the head-kidney and spleen are regarded as the most important secondary lymphoid organs. The detection of tyrosinase activity in lymphoid organs indicates that a link exists between the extracutaneous pigmentary system and the immune system in salmon.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".